Crowd sourced sensor data management systems

ABSTRACT

A sensor data aggregation system is presented. The aggregation system can include a sensor interface configured to obtain sensor data from multiple sensing devices (e.g., cell phone, security cameras, vehicles, etc.) associated with an event. An aggregation server compiles the sensor data into one or more event feeds representing a dynamic, immersive sensory experience of the event. The event feed can then be presented to one or more social groups where social group members can affect the dissemination of sensor data.

This application claims priority to U.S. patent application Ser. No.13/912,567 the following U.S. provisional applications: 61/656,619 filedJun. 7, 2012; 61/675,268, 61/675,263, 61/675,258, and 61/675,271 filedJul. 24, 2012; and 61/676,426, 61/676,431, 61/676,436, 61/676,443, and61/676,452 filed Jul. 27, 2012. These and all other referenced extrinsicmaterials are incorporated herein by reference in their entirety. Wherea definition or use of a term in a reference that is incorporated byreference is inconsistent or contrary to the definition of that termprovided herein, the definition of that term provided herein is deemedto be controlling.

FIELD OF THE INVENTION

The field of the invention is data collection and managementtechnologies.

BACKGROUND

The background description includes information that may be useful inunderstanding the present invention. It is not an admission that any ofthe information provided herein is prior art or relevant to thepresently claimed invention, or that any publication specifically orimplicitly referenced is prior art.

Many people have put forth effort toward reality mining where data iscollected from a user's cell phone to learn more about the user. Forexample, recent work at MIT attempts to identify a user's behaviors orsocial network via observing patterns of use (see URLreality.media.mit.edu/dataset.php).

All publications herein are incorporated by reference to the same extentas if each individual publication or patent application werespecifically and individually indicated to be incorporated by reference.Where a definition or use of a term in an incorporated reference isinconsistent or contrary to the definition of that term provided herein,the definition of that term provided herein applies and the definitionof that term in the reference does not apply.

Interestingly, little to no effort has been directed to aggregatingambient data for a crowd of individuals. The Applicant has appreciatedthat aggregation of sensor data from a crowd, possibly at an event(e.g., sporting event, concert, etc.), provides valuable insight into acrowd dynamic or can be monetized.

Thus, there is still a need for systems and methods by which one canaggregate sensor data from a crowd.

SUMMARY OF THE INVENTION

The inventive subject matter provides apparatus, systems and methods inwhich one can leverage a sensor data aggregation system to construct anevent feed from a plurality of sensing devices. One aspect of theinventive subject matter includes a sensor data aggregation system thatcomprises a sensor interface and an aggregation server. The sensorinterface can be configured to acquire or otherwise obtain sensor datafrom one or more sensing devices. For example, sensor data can beobtained, possibly over a network (e.g., the Internet, cellular network,WWAN, etc.), from smart phones or even security cameras. In morepreferred embodiments, the sensor data is associated with an event,possibly a sporting event or concert. The aggregation server receivesthe sensor data and aggregates the sensor data from the sensing devicesto form an event feed. In some embodiments, the aggregation serverestablishes an event policy that governs how the event feed should beconstructed. The event policy could be established automatically, by anevent owner, by individuals acquiring the sensor data, by thoseobserving the event feeds, or by other techniques. Regardless of how theevent policy is established, the aggregation server constructs the eventfeed according to the rules in the event policy and from the sensordata. The aggregation server can then provide the event feed to one ormore output devices and can instruct the output devices to present theevent feed to one or more users. The output devices can includecomputers, printers, tablets, kiosks, cell phones, or other types ofcomputing devices.

Various objects, features, aspects and advantages of the inventivesubject matter will become more apparent from the following detaileddescription of preferred embodiments, along with the accompanyingdrawing figures in which like numerals represent like components.

BRIEF DESCRIPTION OF THE DRAWING

FIG. 1 is a schematic of sensor data aggregation system.

FIG. 2 is an example of a world-view indicating available events havingevent feeds.

FIG. 3 is an example of a “zoom” in of an available sporting event.

FIG. 4 illustrates that an event can have zones of interest.

FIG. 5 illustrates an event feed as having multiple feeds associatedwith available people of interest.

FIG. 6 illustrates an event feed having image data for specificindividuals.

FIG. 7 illustrates that an event feed can include many different views.

FIG. 8 illustrates an event feed consumed by multiple viewers where theviewers can interact with each other and the feed.

FIG. 9 illustrates that individuals capturing sensor data of an eventcan receive feedback based on one or more event feed metrics.

DETAILED DESCRIPTION

It should be noted that while the following description is drawn to acomputer/server based sensor data management system, various alternativeconfigurations are also deemed suitable and may employ various computingdevices including servers, interfaces, systems, databases, agents,peers, modules, engines, controllers, or other types of computingdevices operating individually or collectively. One should appreciatesuch terms are deemed to computing devices comprising at least oneprocessor configured or programmed to execute software instructionsstored on a tangible, non-transitory computer readable storage medium(e.g., hard drive, solid state drive, RAM, flash, ROM, distributedmemory, etc.). The software instructions preferably configure thecomputing device to provide the roles, responsibilities, or otherfunctionality as discussed below with respect to the disclosedapparatus. In especially preferred embodiments, the various servers,systems, databases, or interfaces exchange data using standardizedprotocols or algorithms, possibly based on HTTP, HTTPS, AES,public-private key exchanges, web service APIs, known financialtransaction protocols, or other electronic information exchangingmethods. Data exchanges preferably are conducted over a packet-switchednetwork, the Internet, LAN, WAN, VPN, or other type of packet switchednetwork.

One should appreciate that the disclosed techniques provide manyadvantageous technical effects including aggregating sensor signals frommultiple sensors and generating one or more network signals capable ofconfiguring devices to present information related to the sensorsignals.

The following discussion provides many example embodiments of theinventive subject matter. Although each embodiment represents a singlecombination of inventive elements, the inventive subject matter isconsidered to include all possible combinations of the disclosedelements. Thus if one embodiment comprises elements A, B, and C, and asecond embodiment comprises elements B and D, then the inventive subjectmatter is also considered to include other remaining combinations of A,B, C, or D, even if not explicitly disclosed.

As used herein, and unless the context dictates otherwise, the term“coupled to” is intended to include both direct coupling (in which twoelements that are coupled to each other contact each other) and indirectcoupling (in which at least one additional element is located betweenthe two elements). Therefore, the terms “coupled to” and “coupled with”are used synonymously. Further, within the context of this document theterms “coupled to” and “coupled with” are used euphemistically to mean“communicatively coupled with” over a network, where two or more devicesare able to communicate with each other over the network, possibly viaone or more intermediary devices.

Overview

One should appreciate that the disclosed systems and method allow usersto remotely participate in an event from anywhere in the world. Theparticipation in the event can be substantially in real-time, gradual,or even delayed as desired by the individual participants. Suchtechniques give rise to the spawning of spontaneous social groups,settings, or experiences through the system's own social sharingcapabilities as well as via all other social media (e.g., Facebook®,Twitter®, Pinterest®, future social networks, etc.). For example,virtual flash mobs, people of common interests, or other groups can bebrought together around a live or even recorded event as if remoteindividuals were there at the time of the event. Through the use ofsensor technology deployed in devices such as smart phones, watches,eyeglasses, clothing, or other sensing device, sensor data or otherexperiences can be created live, utilized, stored, or shared for manypurposes. Example experiences that can benefit from such techniquesinclude entertainment, games, movies/filmmaking, pictures, 3Dexperiences or hologram/media, health applications, tasting foodremotely, exercising remotely, news information and news networks,shopping and commerce—flash mob live shopping event at Tiffany's withgirls directing virtual shoppers, or other events.

Ecosystem

In FIG. 1, system 100 represents a sensor data aggregation system.Contemplated systems include sensor interface 145 (e.g., HTTP server,cellular network, WWAN, etc.) configured or programmed to acquire sensordata 130 from a plurality of sensing devices 120 possibly proximal toevent 110. Sensor data 130 can be sent or otherwise transmitted fromsensing devices 120 over a network (e.g., Internet, cellular network,LAN, VPN, WAN, parts of a personal area network, etc.) to aggregationserver 140 that is preferably configured or programmed to aggregatesensor data 130 into one or more of event feed 160 according to eventpolicy 150 and based on sensor data 130. Event feed 160 can then betransmitted to one or more presentation devices 170 (e.g., computers,tablets, game consoles, game handhelds, cell phones, appliances,vehicles, etc.).

One should appreciate that the disclosed techniques provide forconstruction of a lifelike or virtual experience of event 110 whereindividuals operating presentation devices 170 lack access to event 110can feel like they are participating in event 110 through reception ofevent feed 160. Event feed 160 can include a wide spectrum of modalitiesconstructed from sensor data 130, thus creating an ultra-rich,omni-sensory experience; an experience that can quite possibly exceedthe experience of individuals actually at event 110 because remoteindividuals are able to consumer event feed content from numeroussimulations perspectives as governed by event policy 150.

Individuals or entities controlling sensing devices 120 can beconsidered broadcasters for event 110. The broadcasters collect sensordata 130 can cause sensor data 130 to be transmitted to aggregationserver 140. In some embodiments, broadcasters can be paid a fee inexchange for their services. Further, viewers interacting with event 110via presentation devices 170 can engage one or more broadcasters,possibly in exchange for a fee (e.g., account transactions) to give riseto a dynamic social experience.

Although event 110 is illustrated as a sporting event, one shouldappreciate that event 110 can include a wide variety of experiences.Examples of event 110 can include a concert, a sporting event, a game(e.g., board game, poker game, video game, etc.), a vacation, adisaster, a news story, an expedition, a traffic event, a live event, aflash mob, a shopping event, a reality event, an accident, a medicalemergency, a golf outing, a party (e.g., birthday party, social gatheretc.), a premier, a funeral, a memorial, a commute, or other types ofevent. Event 110 can be directly experienced by any number of sensingdevices 120 associated with any number of individuals at event 110. Forexample, event 110 might include just a few people shopping together,each with their own cell phone operating as sensing device 120. In otherscenarios, a concert for example, event 110 can include thousands, tensof thousands, or more individuals where sensor data 130 is collected anddelivered to aggregation server 140 via a homogenous or heterogeneousmix of thousands of cell phones, cameras, security systems, weathersensors, or other sensing devices.

One should appreciate that the nature of event 110 can impactacquisition of sensor data 130, features of event policy 150, deliveryof event feed 160, or other aspects of system 100. Event 110 can have acorresponding event object stored within a memory aggregation serverwhere the event object comprises event attributes describing the natureof event 110. The event objects can be instantiate before occurrence ofevent 110, possibly by an event manager, or could be instantiated byaggregation server 140 automatically based on observations of sensordata 130. For example, aggregation server 140 can operate according toan event object instantiation rules set that automatically generates anevent object when sensor data 130 satisfies specified criteria. Examplecriteria might depend on a number of sensor data feeds originatingproximal to a GPS coordinate. When sensor data 130 satisfies the eventobject instantiation rules, aggregation server 140 can then instantiatea corresponding event object. Event objects can be instantiated orpopulated with event attributes that then impact the aspects of thesystem where such impacts flow through to the end user at presentationdevices 170

Even attributes describe the nature of corresponding event 110. Eventpolicy 150 could operate as a function of the event attributes, whichimpact how event feeds 160 are curated. Example event attributes includegeo-location coordinates, time stamps, event ownership information,number of transmitting devices, maximum allowed device, digital rightsmanagement information, security triggers or models, cryptographicrequirements, fees or subscription information, type of event, name ofevent, event affiliation, sponsorship information, advertisinginformation, duration of event, or other types of event relatedinformation.

Sensing devices 120 associated with event 110 can also include a broadspectrum of devices. Examples sensing devices 120 can include a vehicle,a cell phone, a pair of eyeglasses, a tablet, a security camera, a gameconsole, or other devices configured to acquire sensor data 130. Forexample, a vehicle involved in a rally race might include anaccelerometer, a temperature gauge, a gas gauge, tire pressure gauge, aGPS sensor, a microphone, a camera, or even a keyboard for enteringdata. During the race, the rally car operates as sensing device 120 canprovide sensor data 130. All sensors are contemplated includingmechanical sensor, biometric sensors, chemical sensors, weather sensor,radar, infrared sensors, or other types of sensors that can constructsensor data 130.

In a similar vein, sensor data 130 represent modalities of humanexperience including modalities outside the ordinary human senses.Example modalities include time data, location data, orientation data,position data, acceleration data, movement data, temperature data,metadata, user data, health data, olfactory data, sound data,kinesthetic data, image data, video data, metric data, biometric data,or other types of modal data. Similarly event feeds 160 generated byaggregation server 140 can also represent event feeds 160 according tosuch modalities, even if the modality is not present in the sensor data.Thus, aggregation server 140 can convert sensor data 130 from onemodality to another modality based on the requirements set forth withinevent policy 150. For example, if sensor data 130 comprises a raw videofeed without sound, event feed 160 can include additional audiblecommentary data that is injected into or overlaid on event feed 160 byaggregation server 140 according to event policy 150.

In view that sensor data 130 can originate from many different sensingdevices 110, one should appreciate that event feed 160 can includemultiple viewing levels based on one or more data streams. Event feed160 can comprise one or more data streams that are constructed fromsensor data 130, possibly in real-time. In some circumstances, eventfeed 160 could be comprises a single data stream (e.g., an HTTP datafeed) of sole event 110. In other circumstances, event feed 160 includemultiple data streams, possibly multiple TCP/IP sessions that canrepresent a single event feed or can represent many different events. Insuch cases, presentation devices 170 are able to present a “zoomed out”view of many different available events.

A zoomed out view is shown in FIG. 2, where one can view a portion of aworld map 200 to see if or where one or more events 210 on theindividual's presentation device. In this example, map 200 presents amultitude of events 210 occurring thorough out Europe. The presentationdevice can receive the event information from the aggregation server asa single stream transporting information on multiple events. As theindividual interacts with events individual, they can be presented moredetailed information as indicated by event 210B. The superimposedcaption presents additional information related to the specific eventand can include a link (i.e., the underlined “TapThere” link) to allowthe presentation device to interact with the specific event.Contemplated captions can be superimposed on maps, an augmented realityoverlay on a displayed image of a real-world scene, or integrated in toa computer game.

Event feeds can be viewed from many different viewing level that allowfor zooming into an event, possibly where the sensor data enables theaggregation server to stitch the sensor data together to form azoom-able event feed. FIG. 3 illustrates a “zoom” in on event 310B fromFIG. 2. One can view potential areas to view by an interactive map asshown in FIG. 2. For example, one can select desired criteria forsearching for available events or event feeds possibly by eventstagged/grouped to a band, a person, a keyword, metadata, individualspresent at the event, celebrity, or other factors. Further, one canchoose how old the event feed is, thus allowing an individual to replayold events. Still further, one can choose by the person broadcasting(follow certain people who broadcast well and rank high amongst a peerrating system), or by quality of the event feed or its associated data.

FIG. 4 illustrates that events 410 can be broke down into event zones ofinterest possibly presented with color codes or other indicia. In theexample shown, the zones of interest are where players of a golftournament are currently located or playing and labeled according to thegolf course's holes. An individual can select one or more event zones toengage with event 410. In some embodiments, event 410 can be presentedvia multiple screens, cell phone and television perhaps, that allow aremote viewer to select an icon or other indicia on one screen to engagewith event feeds via another screen. Event 410 can be presented asmultiple live substantially real-time feeds to an individual via allregistered presentation devices. The live event feeds can presentindications of trending events (rating system) based upon popularity,positions of potential broadcasters open for bid/hire who will capturecontent in exchange for a fee, positions of potential live participatingbroadcasters known by participants (e.g., Facebook friends, Twitterfriends, Pinterest friends, etc), or broadcaster that one can follow or“friend” or have followed in the past, who will capture event data.

As one zooms in or out, or from one feed to another, the system employsa smoothing process (e.g., Bresenham scaling, bilineal interpolation,feature-based image metamorphosis, etc.) is used to provide a seamlesspicture quality when a viewer is watching an event feed broadcast.Should the broadcaster stop broadcasting a the specific sensor data—inthis case defaults/preferences can be set to default to the next closestcamera/broadcaster based on proximity or orientation of the sensor feedrelative to the event. Because pictures and video are taken of an eventobjects (e.g., a person, a vehicle) from multiple angles, a 3D virtualreality or virtual “hologram” can be rendered. Thus the resulting eventfeed can comprise a multi-dimensional representation of the event. Themulti-dimensional representation can include one, two, three, or moredimensions. A four dimensional representation could include a 3Drendering, possibly a voxel-based rendering, that can change in time.The dimensionality can be further extended into other senses, possiblyincluding kinesthetic (e.g., vibration, force feedback, etc.), smell,taste, or other dimensions. Therefore, the event feed could includenon-spatial or non-time related dimensions.

In some embodiments, events can be identified by contextual informationrelated to the event, possibly based on social groups. As an example onecould construct an event feed that operates or comprises a documentary.Such a use-case can be constructed from sensor data associated with agroup of one or more individuals where the sensor data is compiled,according to an appropriate event policy, to present“day-in-the-life-of” content. Such content might be associated with acity, group, person, or event at a university; University of SouthernCalifornia for example. Example groups that are considered of interestinclude a social group, a spontaneous group, a clique, a family, anorganization, a band, a mob (e.g., flash mob, etc.), a crowd, a sportsteam, an entourage, a company, or other group.

FIGS. 5 and 6 illustrates event feeds from specific individuals thatcould be broadcasters or could be people of interest. Specific people,events, topics, or other items of interest can be designated wherein theviewer can either search for these or watch live. Further the event feedor portions of the event feed can be recorded for later viewing.Broadcasters, or potential broadcasters, or their devices can receiverequests from viewers, can automatically attempt to film items ofinterest, or can communicate via a bid/auction process to determine ifthe broadcaster or broadcasting device will actually broadcast per therequest at event 510. Actual pictures of what a viewer is hoping toreceive (see FIG. 6 indicating a picture of interesting people) can betransmitted to a potential broadcaster where the broadcaster, via facialrecognition, optical recognition, audible recognition technology orother sensory technology, can then to find the item of interest. Whenfound, the sensor data associated with the item of interest can be sentto the aggregation server. For example celebrities can be spotted from acrowd or event (again see FIG. 6), and viewers can request thatpotential broadcasters with a certain proximity of an event (GPS)broadcast the celebrity once spotted. Such an approach gives rise to aworldwide user generated or even crowd generated news broadcasts.Further, the disclosed technique can be considered as a form of virtualpaparazzi where remote viewers, in some sense, construct a virtualpresence through which they are able to capture data about theirfavorite personages.

An event feed is considered a dynamic feed allowing remote viewers tointeract, possibly bi-directionally, with the aggregation server,sensing devices, other viewers, or even broadcasters. For example, onecan request that an entity in the event area film an item of interest,possibly where the request includes a payment perhaps generated from an“auction” or “request/bid” process, wherein potential broadcasters agreeto film. Such requests are brokered by the aggregation server and can bequite specific, including a topic, a celebrity, a specific area/GPSlocation, a camera angle, sensing device commands (e.g., movement,positions, focus, etc.), or other type of “direction”. One can alsosubmit trigger criteria to the aggregation server or even the sensingdevices where the trigger criteria cause a capture of the sensor data oreven generation of the event feed. For example, the trigger criteriamight cause a smart phone or even Google® Glass™ to capture sensor dataas triggered by light, time of day, heart rate from heart monitor,altimeter, movement of broadcasting device/gyroscope, noise level,facial recognition, biometric information, movements, hand waving, othercrowd movements, once a particular person or event starts, once certainnoise levels are reached, or other sensory data that the broadcastingdevice or attachments can measure.

One should appreciate that the viewers or other remote individuals canprovide direction to those in the area, where the direction providesinstructions or requests on capturing sensor data via the aggregationserver back to the broadcasters. Thus the event feed can comprise adirected feed under the direction of a plurality of end users. Thedirected feed could be constructed from an individual, based on ratingsfrom the end users, based on votes, or other factors. Further, thesensor data might originate from one or more sensor feed points thatrepresent a specific sensing device or sensor. For example, a feed pointmight include a specific individual's cell phone at the event. To createfurther incentives for the owner of the cell phone the feed point mighthave a monetary value representing the value of the feed point withrespect to capturing the data. A cell phone closest to a stage mighthave a higher monetary value while a cell phone farther away might havea lesser monetary value. The monetary value of the feed point couldcomprise a flat fee, a subscription, a bid, a per-use charge, a locationcharge, a position charge, a tax, a data quantity charge, a sales tax,or other values.

The remote viewer, as well as others, possibly Facebook or other socialmedia friends, can remotely control the broadcasting sensing device.Thus creating a social/friend experience as if they were there together.Such an approach provides for construction of a curated event feed orcurated sensor data. As requests come in from the viewership, theaggregation server relays the requests, possibly after constructing anauction, from the end user or users to the sensing devices. If therequest is picked up or otherwise accepted, then the resulting sensorfeed or event feed is curated by the viewing masses. Further, thecurated feeds can be considered for-fee curated feeds when payment isinvolved. One should appreciate that such curated feeds can be curatedby the end users, according to the event policy, by the individuals atthe event, according to whims of the crowd, or other parameters.

FIG. 7 shows an event feed comprising many different views 710 of anevent; a golf tournament in this case. One should appreciate that a“view” is considered to cover the concept of different modalities beyondthe just visual modality. For example, one “view” might include arepresentation of event temperature data. Views 710 can be considered acrowd curated version of the event data. Many views 710 can be shown andengaged by remote participants where each view can be considered anindividual manageable view objects with respect to the presentationdevices. Thus, the aggregation server can construct an interface (e.g.,API, GUI, etc.) that allows the viewers to interact with views 710collectively or individually. Broadcasts can be organized and access inmany ways subject to restrictions of a corresponding event policy ifany. A ranking algorithm determines what broadcasts are trending andpopular, as well as may be interesting to a viewer based upon theirprofile. The ranking algorithm can operate as a function of the numberof subscribers to a view, amount of money exchanged with respect to theview, number of likes or dislikes, or other factors. Thus, theaggregation server can include one or more trending modules that monitornumber of active viewers, votes, ratings, ranks, or other type of metricdata that can be used to establish a trend.

As discussed previously, the views of an event feed can be governed byone or more event policies. An event policy comprises one or moremanagement functionalities that can dictate how the sensor data isdistributed as the event feed. In some embodiments, the event policymight be non-existing or weakly enforced without substantial interactwith the sensor data. For example, an event policy of a birthday partymight allow aggregation of all data as an event feed with no filteringor editing. However, a sporting event such as a USC Trojan's Rose Bowlevent might require specific management to ensure digital rights areenforced properly. Therefore, the event policy can comprise rules fromone or more participants in the ecosystem. Event policies can representrules from an owner of the event, from an end user, from rules generatedautomatically from multiple users (e.g., votes, requests, ratings,etc.), or from other entities. Example management functionality withinan event policy can include prioritizing content, filtering content,injecting content, deleting content, routing cogent, sharing content,authorizing content, managing content, curating content, schedulingcontent, programming content, analyzing content, or other types ofmanagement. Through such techniques, the event feed can be quite adynamic, social experience for participants.

FIG. 8 illustrates a possible shared experience among end users. Theremote viewers, as well as others (such as Facebook/social mediafriends) can remotely control the broadcasting device to construct adesirable event feed as illustrated thereby creating a social/friendexperience as if they were there together. In the example shown, the twoindividuals are participating in a golf event where the event feedindicates at least a portion of the crowd has a different focal pointthan the main event; the focal point being the girls rather than thegolfers.

One should appreciate that the inventive subject matter is alsoconsidered to include identification or even discovery of focal pointswithin event other that the main event. For example, an audience at anoutdoor concert would likely have a core or main focal point on thestage. However, other minor focal points might arise and become ofinterest to remote participants; perhaps a person dancing to the musicof interest. The aggregation server can identify the focal point bymonitoring the sensor data stream possibly by determining locations ofsensing device and their position or orientation. To continue theexample of the dancer, the aggregation server might detect that athreshold number of cell phones are pointed at a common location otherthan the stage. The aggregation server can then take the sensor datafrom the cell phones to construct a view within the event feedcorresponding to the dancer focal point. Thus, the focal point can beconsidered a crowd or mob focal point. Such focal points can comprisesensor data related to at least one of a topic, a celebrity, asub-event, a location, an area, an object, or other item of commoninterest.

As the aggregation server delivers the event feed, the server can applyone or more algorithms to take input from viewer who canrate/dynamically rate broadcasters, broadcasts, or other items in theevent feed. Such metrics can then provide useful trending information toviewers to provide the best viewing experience. For example, a minorfocal point might arise dynamically and then the ratings of the minorfocal point could trend upwards, which causes its presence in the eventfeed to become more prevalent. Such metric data can also be used forvarious forms of event analytics. Contemplated analytics can be used togenerate advertising revenue, provide an indication of problem areas atevent locations, identify broadcasters of high interest, identify activeviewers, determine demographics, or other interesting purposes.

Still further, the disclosed techniques give rise to dynamic socialsharing. Viewers can interact, share, or rate via avatars on screen andother means as illustrated in FIG. 8. Ecommerce activities can betriggered by this activity just as it would if people were actuallyphysically at an event. Thus the event feed can comprise various formsof transaction data including commercial transaction data. For example,the event feed can include product information or vendor informationwhere the product can be purchased. Further, the event feed can includeaccount information by which a participant can purchase the product.Example transaction data can represent an account, a good, a service, anadvertisement, a purchasable product, or other types of items.

As illustrated in FIG. 9, broadcasters, or other individuals capturingsensor data, can receive dynamic feedback; possibly before, during, orafter capturing the sensor data. In the example show, a broadcastingusing their cell phone as a sensing device receive trending information,ratings, number of viewers, incoming requests, auction information, orbid data. All types of feedback are contemplated. Further, the feedbackcan include alerts, request for capturing data associated with items intheir area based on GPS coordinates, or other factors. In someembodiments, the media can submit bids to broadcasters to capture data.For example, TMZ® might submit one or more bids, or other form ofpayments, to individuals at an event where the payments indicate adesire for requested videos or pictures. Such an approach is considereduseful for capturing information associated news event, celebrities,film projects, or other activities. An astute reader will appreciate thedisclosed techniques give rises to altering the perception of the worldthrough live, truthful broadcasting.

The disclosed techniques have many use-cases beyond those discussedabove. One possibility can include using the incentive mechanisms tosearch for lost children. Broadcasters are incentivized to capturesensor data where a child may have been lost and viewers areincentivized to monitor event feeds to see if they can spot the child.In a different vein, an event televised on ESPN® could include views ofan event feed of people participating in a tailgate party that might beof interest to the viewership.

The sensor data aggregation system can also be considered as a virtualsensor array management system. The aggregation server can monitorsensor feeds from many devices and identify an event possibly inreal-time. The aggregation server can then construct a virtual sensorarray from the available sensing devices proximal to the event, orsimply related to the event. The virtual sensor array can be boundtogether possibly through a hierarchal addressing scheme or throughother organization structures. For example, the aggregation serverscould arrange the virtual array according to modality of sensor data,relative location to one or more focal points, according to broadcasterratings, or other scheme. In such embodiments, the aggregation servercan function as a virtual sensor array management engine that maintains,to within bounds of any pending event policy, coherency of the array.Management capabilities can include adding sensing devices to the array,removing sensing devices from the array, filling gaps in sensor data(e.g., stitching, interpolation, etc.), requesting new sensing devices,maintain rights, or other actions. One should appreciate that thevirtual sensor array can be quite dynamic that changes with time.

In some embodiments, the numbers expressing quantities of ingredients,properties such as concentration, reaction conditions, and so forth,used to describe and claim certain embodiments of the invention are tobe understood as being modified in some instances by the term “about.”Accordingly, in some embodiments, the numerical parameters set forth inthe written description and attached claims are approximations that canvary depending upon the desired properties sought to be obtained by aparticular embodiment. In some embodiments, the numerical parametersshould be construed in light of the number of reported significantdigits and by applying ordinary rounding techniques. Notwithstandingthat the numerical ranges and parameters setting forth the broad scopeof some embodiments of the invention are approximations, the numericalvalues set forth in the specific examples are reported as precisely aspracticable. The numerical values presented in some embodiments of theinvention may contain certain errors necessarily resulting from thestandard deviation found in their respective testing measurements.

As used in the description herein and throughout the claims that follow,the meaning of “a,” “an,” and “the” includes plural reference unless thecontext clearly dictates otherwise. Also, as used in the descriptionherein, the meaning of “in” includes “in” and “on” unless the contextclearly dictates otherwise.

The recitation of ranges of values herein is merely intended to serve asa shorthand method of referring individually to each separate valuefalling within the range. Unless otherwise indicated herein, eachindividual value is incorporated into the specification as if it wereindividually recited herein. All methods described herein can beperformed in any suitable order unless otherwise indicated herein orotherwise clearly contradicted by context. The use of any and allexamples, or exemplary language (e.g. “such as”) provided with respectto certain embodiments herein is intended merely to better illuminatethe invention and does not pose a limitation on the scope of theinvention otherwise claimed. No language in the specification should beconstrued as indicating any non-claimed element essential to thepractice of the invention.

Groupings of alternative elements or embodiments of the inventiondisclosed herein are not to be construed as limitations. Each groupmember can be referred to and claimed individually or in any combinationwith other members of the group or other elements found herein. One ormore members of a group can be included in, or deleted from, a group forreasons of convenience and/or patentability. When any such inclusion ordeletion occurs, the specification is herein deemed to contain the groupas modified thus fulfilling the written description of all Markushgroups used in the appended claims.

It should be apparent to those skilled in the art that many moremodifications besides those already described are possible withoutdeparting from the inventive concepts herein. The inventive subjectmatter, therefore, is not to be restricted except in the scope of theappended claims. Moreover, in interpreting both the specification andthe claims, all terms should be interpreted in the broadest possiblemanner consistent with the context. In particular, the terms “comprises”and “comprising” should be interpreted as referring to elements,components, or steps in a non-exclusive manner, indicating that thereferenced elements, components, or steps may be present, or utilized,or combined with other elements, components, or steps that are notexpressly referenced. Where the specification claims refers to at leastone of something selected from the group consisting of A, B, C . . . andN, the text should be interpreted as requiring only one element from thegroup, not A plus N, or B plus N, etc.

What is claimed is:
 1. A sensor data aggregation system comprising: asensor interface configured to acquire sensor data from a plurality ofsensing devices at an event; and an aggregation server coupled with thesensor interface and configured to: aggregate the sensor data from theplurality of sensing devices; construct a virtual sensor array thatcomprises the plurality of sensing devices; establish an event policygoverning dissemination of the sensor data; establish a social policygoverning one or more social media parameters associated with the sensordata, wherein the social media parameters enable one or more remoteviewers to remotely control one or more sensing devices of the pluralityof sensing devices, wherein the remote viewer includes at least onesocial media friend, and wherein the social policy allows the one ormore remote viewer to directly interact with the sensor data of thesensing devices, with at least one of one or more avatars and one ormore ecommerce activities associated with the event according to thesocial policy; construct an event feed based on at least one of theevent policy, the aggregated sensor data, and the social policy suchthat the event feed can be interacted with by the one or more remoteviewers; instruct at least one device to present the event feed; andmaintain a coherency of the virtual sensor array based on the eventpolicy by: determining that a gap in sensor data exists; and addingsensing devices to the array.
 2. The system of claim 1, wherein theevent includes at least one of the following: a concert, a sportingevent, a game, a vacation, a disaster, a news story, an expedition, atraffic event, a live event, a flash mob, a shopping event, a realityevent, and an accident.
 3. The system of claim 1, wherein the sensingdevices comprise at least one of the following sensor platforms: avehicle, a cell phone, a pair of eyeglasses, a tablet, a securitycamera, and a game console.
 4. The system of claim 1, wherein the eventpolicy represents rules from the event owner.
 5. The system of claim 1,wherein the event policy represents rules from an end user.
 6. Thesystem of claim 1, wherein the event policy represents rulesautomatically generated according to a plurality of end users.
 7. Thesystem of claim 1, wherein the event feed comprises a focal pointderived from the aggregated sensor data.
 8. The system of claim 7,wherein the focal point comprises a mob focal point.
 9. The system ofclaim 7, wherein the focal point comprises at least one of thefollowing: a topic, a celebrity, a sub-event, a location, an area, andan object.
 10. The system of claim 1, wherein the sensor data comprisemulti-modal data.
 11. The system of claim 10, wherein the sensor datacomprises at least one of the following types of data: time data,location data, orientation data, position data, acceleration data,movement data, temperature data, metadata, user data, health data,olfactory data, sound data, kinesthetic data, image data, video data,metric data, and biometric data.
 12. The system of claim 1, wherein theevent feed comprises multiple viewing levels.
 13. The system of claim12, wherein the multiple viewing levels support zoom.
 14. The system ofclaim 12, wherein the multiple viewing levels comprise image datastitched together from at least some of the aggregated data.
 15. Thesystem of claim 1, the aggregation server is further configured to relaysensor data request from an end user to at least one of the plurality ofsensing devices.
 16. The system of claim 15, wherein the sensor feedcomprises curated data.
 17. The system of claim 16, wherein the curateddata is curated by end users.
 18. The system of claim 16, wherein thecurated data is for-fee curated data.
 19. The system of claim 1, whereinthe event feed comprises a bi-directional feed.
 20. The system of claim1, wherein the event feed comprises a multi-dimensional representationof the event.